Normalized compound random measures are flexible nonparametric priors for related distributions. We consider building general nonparametric regression models using normalized compound random measure mixture models. Posterior inference is made using a novel pseudo-marginal Metropolis-Hastings sampler for normalized compound random measure mixture models. The algorithm makes use of a new general approach to the unbiased estimation of Laplace functionals of compound random measures (which includes completely random measures as a special case). The approach is illustrated on problems of density regression.
"Modelling and Computation Using NCoRM Mixtures for Density Regression." Bayesian Anal. 13 (3) 897 - 916, September 2018. https://doi.org/10.1214/17-BA1072